
Overview of the course structure and goals
Importance of algorithmic trading in the crypto market
Basic concepts of cryptocurrency and blockchain technology
Differences between cryptocurrency and traditional assets
Key trading terms and concepts (market orders, limit orders, exchanges)
Introduction to risk and reward in trading
What algorithmic trading is and its benefits
Key differences from manual trading
Why Python is commonly used for trading automation
Quick overview of Python's versatility for trading
Step-by-step guide to install Python and Freqtrade
Introduction to key Python libraries for algorithmic trading
Overview of Freqtrade and its features
Configuring a demo trading environment
Structure of a basic trading strategy (entry, exit, stop-loss)
Code a basic algorithmic crypto trading strategy in python, using candle classification, moving averages, volume spread, and standard deviation analysis, with mplfinance visualizations for long and short entries.
Integrate the candle classification strategy into the freqtrade workflow and deploy automated Bitcoin long trades using a data frame, pandas, numpy, and volume spread analysis.
Refine an RSI based candle strength classification to assess whether price action tells the truth, plot RSI candlesticks, and develop threshold-based buy and sell signals in algorithmic crypto trading.
Overview of common indicators (moving averages, RSI)
How indicators help in decision-making
Classify market trends with a weighing-machine approach, labeling very strong bullish, strong bullish, moderate bullish, and sideways markets; apply RSI cues and freqtrade backtesting to craft trend-based strategies.
Step-by-step guidance to create a basic trend-following strategy
Advance building a simple trading strategy by integrating sentiment, sessions, volume, and price bands, plus stop losses and custom exits, backtesting, and result analysis.
Code and backtest a fair value gap trading strategy using Python freqtrade, testing long and short setups on 15-minute Binance Ethereum data. Learn stop loss, take profit, and trailing exits.
Are you ready to dive into the world of algorithmic trading and unlock the potential of automated cryptocurrency trading? This beginner-friendly course, "Algorithmic Crypto Trading for Beginners: Make Money with Python and Freqtrade," is designed to guide you through the essentials of cryptocurrency, trading basics, and the exciting field of algorithmic trading.
In this course, you'll learn how to use Python and Freqtrade, a powerful open-source trading bot, to automate your crypto trading strategies. We start with the fundamentals, covering key concepts in cryptocurrency and trading, so even complete beginners can follow along. You’ll explore why algorithmic trading is a game-changer for traders, discover the basics of trading bots, and set up a solid foundation to understand and create your own strategies.
Once you’re comfortable with the basics, we’ll move into hands-on coding exercises where you'll create your first trading strategy, backtest it with historical data, and optimize it for better performance. You’ll also learn essential risk management techniques to protect your assets and increase your chances of long-term success. Finally, we'll guide you through deploying your trading bot in a simulated environment, so you can confidently transition to live trading when ready.
By the end of this course, you’ll have the skills to create, test, and optimize algorithmic trading strategies that work for you. Join us, and take your first steps towards profitable crypto trading!